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Record W4416289754 · doi:10.1200/cci-25-00140

Using Real-World Data to Determine Acute Chemotherapy Emetogenicity in Pediatric Patients

2025· article· en· W4416289754 on OpenAlex
L. Lee Dupuis, Terrence Lo, Yi Man, Lillian Sung, Mina Tadrous, Cherry Chu

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJCO Clinical Cancer Informatics · 2025
Typearticle
Languageen
FieldMedicine
TopicNausea and vomiting management
Canadian institutionsOntario Drug Policy Research NetworkInstitute for Clinical Evaluative SciencesUniversity of TorontoSickKids FoundationHospital for Sick ChildrenWomen's College Hospital
Fundersnot available
KeywordsChemotherapyPediatric cancerSelection (genetic algorithm)AntiemeticClinical trialCancer chemotherapy

Abstract

fetched live from OpenAlex

PURPOSE: Direct pediatric information to inform chemotherapy emetogenicity in pediatric patients is limited. Therefore, the framework for antiemetic selection is uncertain. This study classified the acute emetogenicity of chemotherapy regimens in pediatric patients using data extracted from the electronic health record (EHR). METHODS: This retrospective, single-institution study extracted data from the EHR of patients age 0 to 18 years who received chemotherapy during an inpatient admission from July 1, 2018, through February 29, 2024. Data were organized by patient and chemotherapy block including patient demographics; date, time, and route of chemotherapy and antiemetic administration; and date and time of vomiting. When at least 30 patients received the same chemotherapy and antiemetics during a chemotherapy block, the proportion of chemotherapy blocks where patients experienced complete, partial, or failed chemotherapy-induced vomiting control was determined. Chemotherapy regimen emetogenicity was assigned using a revision of an accepted pediatric chemotherapy emetogenicity classification framework that adjusted for antiemetic administration. RESULTS: Seven thousand two hundred ninety-six chemotherapy blocks in 1,386 patients were identified. The emetogenicity of 25 chemotherapy regimens was classified: highly (7), moderately (5), low (10), and minimally (3) emetogenic. For 19 of these, no direct pediatric information was previously available. In five, our findings confirm the previous pediatric emetogenicity classification. Relative to emetogenicity classifications for adults, our findings led to classifications that were higher (seven regimens), lower (one regimen), or the same (four regimens). CONCLUSION: We have applied a novel method, EHR data extraction, to provide direct pediatric evidence to classify chemotherapy emetogenicity. Increasing the certainty of chemotherapy emetogenicity facilitates effective antiemetic selection for pediatric patients. This method may be applied in multi-institution studies to increase the number of chemotherapy regimens whose emetogenicity is classified using direct pediatric evidence.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.573

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.264
GPT teacher head0.507
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it